LEADERBOARD

After Round 5, 2025.

Tips Bits MAE Correct
Glicko Ratings

2 8 5 7 7 7

36 11.14 26.90 81.8%
Matter of Stats

2 8 4 8 7 7

36 10.85 27.46 81.8%
Aggregate

2 8 5 7 7 7

36 10.40 27.42 81.8%
Drop Kick Data

2 8 5 6 7 7

35 12.20 25.90 79.5%
Informed Stats

1 8 6 7 6 7

35 12.03 28.30 79.5%
ZaphBot

1 8 6 7 7 6

35 11.54 28.18 79.5%
Don't Blame the Data

2 8 3 7 7 8

35 11.12 27.77 79.5%
Winnable

1 8 6 6 7 7

35 10.68 27.52 79.5%
Live Ladders

2 7 3 8 7 8

35 10.36 28.75 79.5%
s10

2 8 5 7 7 6

35 10.24 27.71 79.5%
Cheap Stats

1 8 5 7 7 7

35 8.66 26.52 79.5%
AFLalytics

2 7 5 7 7 6

34 10.35 27.23 77.3%
Punters

1 8 5 7 7 6

34 9.36 27.47 77.3%
AFL Lab

2 8 4 6 7 7

34 8.53 28.96 77.3%
The Cruncher

2 7 5 6 7 6

33 12.05 26.07 75.0%
Wheelo Ratings

1 8 5 6 7 6

33 11.84 26.56 75.0%
What Snoo Thinks

1 8 3 7 6 8

33 10.94 27.99 75.0%
The Wooden Finger

2 8 4 7 5 7

33 10.79 29.57 75.0%
footycharts

2 7 3 8 7 6

33 9.48 29.21 75.0%
Stattraction

2 7 4 8 6 6

33 8.85 29.40 75.0%
Squiggle

1 7 5 8 7 5

33 8.77 28.91 75.0%
Hyperion

1 7 5 6 6 7

32 9.73 28.77 72.7%
Massey Ratings

1 8 5 6 6 6

32 9.08 29.00 72.7%
AFL Scorigami

2 8 4 6 5 6

31 9.59 29.09 70.5%
The Footycast

1 7 5 6 6 6

31 6.38 31.09 70.5%
Elo Predicts!

1 7 3 6 7 6

30 8.10 30.32 68.2%
Graft

1 5 5 6 7 6

30 7.29 29.36 68.2%
PlusSixOne

1 6 2 6 7 6

28 3.58 32.76 63.6%

"Tips" is the number of correct tips. Draws are counted as correct.

"Bits" from Monash University Probabilistic Footy Tipping rewards tipsters for saying a win was more likely and punishes them for saying it was unlikely. Higher is better.

"MAE" is Mean Absolute Error, which is the average difference between predicted and actual margins. Lower is better.

"Correct" is the percentage of correct tips, i.e. "Tips" divided by the total number of tips provided (which is normally also the number of games played, assuming the model tips all games).

"†number" indicates missing tips: This source did not provide a tip for the specified number of games, which can distort all three metrics. Although missing a game is usually bad for the tipster, it can cause an undeserved boost to Bits and MAE when the missed game is an upset.

[+] Bits, MAE, Tips... which is best?

Tips is what most people care about: How many winners did you pick? So it's the primary variable for the Squiggle leaderboard. But there's a fair bit of luck involved in tipping 50/50 games, so it's hard to know whether a high Tips score is due to skill or good fortune.

Bits are earned by confident correct tips, lost by confident incorrect tips, and not much happens either way for fence-sitting 50/50 tips. The added dimension of "confidence" means Bits are less influenced by luck, so high scores are likely to indicate models that are good performers over the long-term.

MAE (or Mean Absolute Error) measures how far, on average, margin tips are from the actual margin. (Lower MAE scores are better.) It's hard to fluke a good MAE, because your tips have to be consistently close to the real margins, and therefore it's probably the best of the three metrics at measuring a model's underlying forecasting skill. However, it doesn't measure whether anyone is getting the winners right, which means it's not directly tracking the most important factor.

By Round

By Team

Adelaide Adelaide Adelaide Brisbane Lions Brisbane Lions Brisbane Lions Carlton Carlton Carlton Collingwood Collingwood Collingwood Essendon Essendon Essendon Fremantle Fremantle Fremantle Geelong Geelong Geelong Gold Coast Gold Coast Gold Coast Greater Western Sydney Greater Western Sydney Greater Western Sydney Hawthorn Hawthorn Hawthorn Melbourne Melbourne Melbourne North Melbourne North Melbourne North Melbourne Port Adelaide Port Adelaide Port Adelaide Richmond Richmond Richmond St Kilda St Kilda St Kilda Sydney Sydney Sydney West Coast West Coast West Coast Western Bulldogs Western Bulldogs Western Bulldogs
Glicko Ratings 80% 1.5 25.8 100% 2.7 13.7 60% -0.8 23.3 100% 1.6 31.0 100% 1.1 24.4 80% 1.7 25.0 60% 0.6 24.0 100% 1.7 37.5 100% 1.8 18.1 80% 0.6 16.0 80% 1.0 30.9 80% 1.9 33.8 60% -0.2 41.3 80% 1.2 37.1 60% 0.4 33.2 80% 0.8 21.5 100% 3.5 36.7 80% 1.0 12.4
Matter of Stats 80% 1.1 30.7 100% 2.1 16.1 80% 0.7 16.9 80% 0.7 34.6 100% 0.7 27.7 80% 1.7 23.6 60% 0.6 22.5 100% 1.7 37.2 100% 1.7 18.7 80% 0.8 15.5 80% 0.5 33.0 80% 1.8 35.8 60% 0.3 41.2 80% 1.8 34.5 60% 0.4 34.4 80% 0.5 21.2 100% 3.5 38.6 80% 1.0 14.0
Aggregate 80% 1.4 26.4 100% 2.4 13.0 80% 0.3 18.9 100% 0.8 33.7 75% 0.7 27.1 80% 1.6 25.9 60% 0.7 23.8 100% 1.3 39.2 100% 1.6 20.6 80% 0.9 13.4 80% 0.4 35.1 80% 1.8 34.1 40% 0.0 41.7 80% 1.5 35.7 60% 0.3 35.4 80% 0.6 21.1 100% 3.4 39.2 100% 1.1 11.4
Drop Kick Data 80% 1.6 26.0 100% 2.8 13.5 60% 0.4 15.8 100% 1.3 30.8 75% 1.0 25.0 80% 1.5 24.6 60% 0.8 21.9 100% 1.6 37.0 100% 2.1 19.4 80% 1.3 11.4 80% 0.9 33.7 80% 1.7 33.8 40% -0.4 43.5 80% 1.6 35.4 60% 0.3 34.3 80% 1.1 20.9 100% 3.7 31.9 80% 1.2 9.3
Informed Stats 100% 2.3 26.0 100% 3.3 30.2 80% -0.2 15.8 60% 0.3 37.8 75% 0.8 28.8 80% 2.2 19.4 80% 0.4 28.8 100% 2.5 27.8 80% 1.2 21.2 80% 0.8 16.8 80% 0.1 37.0 80% 2.3 36.6 40% -0.3 42.4 80% 1.0 39.0 60% -0.0 35.4 80% 1.2 22.6 100% 4.4 29.2 80% 1.6 14.6
ZaphBot 100% 1.7 21.8 100% 2.9 14.8 80% 1.1 17.6 80% 0.8 35.2 50% 0.2 38.8 100% 1.9 24.4 80% 0.9 23.0 100% 1.3 35.8 100% 2.0 22.8 60% 1.1 21.2 60% 0.6 36.2 80% 2.1 34.8 40% -0.9 46.4 80% 2.1 32.0 60% -0.5 37.6 60% 0.8 23.6 100% 3.5 35.6 100% 1.5 9.4
Don't Blame the Data 80% 1.2 28.7 100% 2.5 16.5 80% 0.5 18.4 80% 0.7 34.3 50% 0.6 27.9 80% 1.4 26.8 80% 1.0 21.9 100% 1.6 36.6 100% 1.5 22.7 80% 1.1 13.2 80% 0.8 31.2 80% 2.2 35.3 40% 0.1 40.6 80% 1.8 36.0 60% 0.0 36.9 80% 0.9 18.6 100% 3.3 40.4 80% 1.0 15.9
Winnable 80% 2.1 22.8 100% 2.5 15.0 80% -0.6 21.0 80% 0.8 36.3 75% 1.2 25.2 80% 1.2 25.7 60% 0.9 26.6 75% 0.9 45.4 80% 1.1 29.2 80% 1.7 16.2 80% 0.9 32.5 100% 2.0 31.6 40% 0.2 36.7 80% 1.2 29.5 60% 0.5 32.0 80% 0.1 23.2 100% 3.7 38.0 100% 0.9 11.5
Live Ladders 80% 1.1 31.4 100% 2.0 10.0 80% 0.8 18.6 80% 1.0 32.8 75% 0.5 30.2 80% 1.5 28.4 80% 0.8 23.8 100% 1.5 40.8 80% 1.6 26.8 80% 1.4 15.2 60% -0.2 38.6 80% 1.7 36.0 60% 0.4 40.2 80% 1.9 33.4 60% 0.2 36.6 80% 0.7 20.4 100% 3.0 44.2 80% 1.1 12.8
s10 80% 1.5 25.9 100% 2.4 12.5 80% 0.6 18.2 100% 1.0 32.9 50% 0.6 28.9 80% 1.5 26.3 60% 0.7 22.7 100% 1.3 39.9 100% 1.5 22.3 80% 0.9 14.2 60% 0.1 36.7 80% 1.7 34.5 40% -0.1 42.5 80% 1.6 35.6 60% 0.1 36.0 80% 0.8 20.6 100% 3.3 40.2 100% 1.0 11.6
Cheap Stats 80% 1.1 25.4 100% 2.4 10.0 80% -0.1 17.8 80% 0.9 32.6 75% 0.6 27.2 80% 1.4 26.2 60% 0.1 26.2 100% 1.2 38.5 80% 1.5 20.4 80% 0.5 15.0 80% 0.6 33.8 80% 1.2 32.2 40% -0.2 42.0 80% 0.8 36.8 60% 0.3 33.2 80% 0.4 22.4 100% 3.3 36.4 100% 1.4 3.8
AFLalytics 80% 1.4 27.8 100% 1.9 12.4 60% 0.2 20.2 100% 1.4 30.7 75% 0.7 27.3 80% 1.7 24.7 60% 0.8 22.6 100% 1.2 43.3 80% 1.5 20.3 80% 0.6 16.3 40% 0.3 35.5 80% 1.8 33.0 60% 0.5 39.4 80% 1.6 34.6 60% 0.5 33.7 80% 0.1 23.7 100% 3.3 38.6 80% 1.1 9.1
Punters 80% 1.4 26.2 100% 2.6 15.2 80% -0.9 20.8 80% 1.3 35.0 50% 0.8 27.0 80% 1.9 22.8 60% 0.0 27.4 100% 1.2 40.7 80% 1.7 18.8 80% 0.8 14.4 60% 0.4 36.6 80% 1.5 33.7 40% -0.2 41.3 80% 0.6 37.0 60% 0.2 33.9 80% 0.3 22.6 100% 3.6 36.0 100% 1.6 7.5
AFL Lab 100% 1.5 25.8 100% 2.0 15.3 80% 1.1 15.4 80% 0.5 35.6 75% 0.7 26.6 80% 0.9 28.8 80% 1.2 19.9 75% 0.9 43.4 80% 0.7 26.6 80% 0.9 11.8 60% -0.2 39.0 80% 1.3 39.1 40% -0.0 40.9 80% 1.5 34.9 40% -0.3 38.9 80% 1.2 18.0 100% 2.4 47.2 80% 0.8 16.5
The Cruncher 80% 2.0 22.1 100% 3.0 13.7 60% -0.8 21.7 100% 1.4 33.3 50% 1.1 24.3 80% 2.1 22.4 60% 0.7 23.7 100% 1.7 35.9 80% 1.8 17.9 80% 0.9 15.0 40% 0.5 34.2 80% 2.0 31.5 40% -0.2 42.3 80% 1.0 37.7 60% 0.6 31.3 80% 1.0 20.8 100% 4.0 34.3 80% 1.2 8.6
Wheelo Ratings 80% 2.0 22.5 100% 2.9 14.8 60% -0.2 18.8 80% 1.4 33.6 50% 0.8 28.9 80% 1.7 24.4 60% 0.8 22.8 100% 1.5 38.0 80% 1.6 19.8 80% 1.1 13.5 60% 0.8 34.6 80% 2.2 29.6 40% -0.5 42.6 80% 1.3 36.0 60% 0.3 34.0 80% 1.3 19.3 100% 3.4 36.6 80% 1.3 11.0
What Snoo Thinks 80% 0.9 28.8 100% 2.0 13.2 80% 0.4 19.7 80% 0.4 36.5 50% 0.8 27.9 60% 1.6 26.8 80% 1.1 20.3 100% 1.5 35.5 100% 2.1 21.8 60% 0.6 16.9 80% 1.3 30.7 80% 2.3 34.4 40% 0.1 42.6 80% 1.5 37.5 60% 0.4 35.8 60% 0.5 20.7 100% 3.6 40.0 60% 0.8 16.2
The Wooden Finger 80% 1.4 27.4 100% 2.7 21.4 80% 0.1 23.0 60% 0.2 37.4 75% 1.0 31.2 60% 1.6 23.8 80% 0.7 23.2 75% 1.3 36.2 100% 2.6 20.2 80% 1.5 21.6 80% 0.3 37.6 80% 1.9 39.4 40% -0.9 44.4 80% 1.1 36.8 60% 0.1 34.8 60% 1.1 18.2 100% 3.9 37.0 60% 1.0 20.2
footycharts 60% 0.9 33.0 100% 2.1 13.5 80% 0.8 17.9 80% 0.4 36.0 75% 0.6 28.2 80% 1.0 29.6 60% 1.0 22.5 100% 1.3 43.2 60% 1.2 25.9 80% 1.3 13.4 60% 0.4 33.7 80% 1.9 35.4 60% 0.5 39.3 80% 1.7 36.4 40% 0.1 37.7 80% -0.1 24.4 100% 2.9 45.2 80% 1.0 13.2
Stattraction 60% 0.6 33.1 100% 2.1 8.6 80% 0.6 18.9 40% -0.1 40.4 75% 0.7 29.3 80% 1.3 28.7 60% 0.2 27.5 100% 1.3 38.2 100% 1.7 26.1 80% 0.9 16.9 80% 0.4 35.7 80% 1.8 34.7 40% -0.1 42.8 80% 1.7 35.5 60% -0.2 39.5 80% 0.6 20.2 100% 3.2 40.6 60% 0.9 14.1
Squiggle 80% 1.8 24.1 100% 2.3 17.4 80% -0.8 24.2 60% 1.0 37.4 100% 1.1 26.9 80% 1.2 27.4 60% 0.3 26.0 100% 1.4 39.9 40% 0.3 30.2 80% 0.8 16.5 60% 0.1 36.5 80% 1.7 31.0 60% 0.5 38.2 80% 0.4 39.3 40% 0.6 31.7 60% 0.4 24.7 100% 3.0 43.2 100% 1.4 7.5
Hyperion 100% 1.1 28.2 80% 2.7 14.6 80% 0.4 20.0 60% 0.6 34.8 75% 0.5 29.2 80% 1.7 26.6 80% 1.6 25.4 75% 1.0 40.8 100% 2.1 20.0 60% -0.1 17.6 60% 0.1 40.2 80% 2.0 34.2 40% -0.6 42.8 80% 1.7 34.4 60% 0.5 35.2 40% -0.1 22.0 100% 3.1 42.6 60% 1.2 11.8
Massey Ratings 80% 1.1 26.7 100% 1.8 13.5 80% 0.9 17.5 80% 1.0 33.7 50% 0.4 29.5 80% 1.5 28.5 60% 0.5 24.9 75% 0.9 40.2 100% 1.6 22.9 60% 0.5 17.1 40% -0.3 39.9 80% 1.6 37.1 40% 0.1 43.1 80% 1.6 38.9 60% 0.3 36.7 80% 0.5 20.7 100% 3.6 38.5 60% 0.8 14.9
AFL Scorigami 60% 0.8 30.2 80% 1.9 11.2 80% 0.7 18.9 60% 0.6 35.7 75% 0.9 26.6 60% 1.3 30.9 40% 0.4 25.2 75% 1.0 42.8 100% 1.4 26.3 80% 1.5 11.8 80% 0.7 32.7 80% 1.3 39.9 40% 0.3 41.0 80% 1.4 38.1 60% 0.4 36.1 60% 0.4 23.1 100% 3.2 44.0 60% 0.8 11.3
The Footycast 80% 1.1 30.7 80% 1.8 16.4 60% 0.1 21.6 80% 0.7 36.4 75% 0.2 30.1 80% 0.9 32.2 60% -0.1 27.4 75% 1.2 44.8 100% 1.5 25.8 60% 0.2 20.8 40% -0.6 39.5 80% 1.5 37.5 60% -0.3 42.8 80% 1.6 32.8 60% -0.1 35.6 60% 0.4 24.5 100% 3.5 40.4 40% -0.9 22.8
Elo Predicts! 80% 1.1 26.6 100% 2.5 12.8 80% 0.3 25.8 60% 0.5 37.0 25% 0.2 35.8 80% 1.6 25.0 80% 0.8 26.4 75% 0.9 39.2 80% 1.4 25.6 60% 0.2 19.8 20% -0.9 42.8 80% 1.4 33.2 40% 0.1 45.2 80% 1.4 38.0 60% -0.0 38.8 40% 0.3 22.4 100% 3.2 44.2 80% 1.2 10.0
Graft 80% 1.2 31.0 80% 1.7 21.4 80% 0.1 20.8 40% 0.3 36.4 75% 0.3 29.8 100% 1.7 20.8 60% 0.1 28.6 75% 1.2 36.5 80% 1.6 14.8 60% 0.3 17.6 40% -0.9 43.4 80% 1.4 41.6 20% 0.2 40.0 80% 1.3 33.4 60% 0.1 35.4 40% -0.5 27.0 100% 3.6 34.2 80% 1.0 17.4
PlusSixOne 60% 0.4 33.0 80% 0.9 10.6 40% -0.0 25.1 80% 0.3 37.1 50% 0.1 33.1 80% 0.7 34.0 60% 0.6 26.0 75% 0.2 47.9 60% 0.4 31.5 60% 0.2 20.0 20% -0.4 42.2 80% 1.1 40.1 80% 0.4 40.9 80% 0.5 46.6 40% 0.1 38.0 40% -0.4 27.1 100% 1.6 47.5 60% 0.6 12.0